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Carl Foster, Jose A. Rodriguez-Marroyo and Jos J. de Koning

Training monitoring is about keeping track of what athletes accomplish in training, for the purpose of improving the interaction between coach and athlete. Over history there have been several basic schemes of training monitoring. In the earliest days training monitoring was about observing the athlete during standard workouts. However, difficulty in standardizing the conditions of training made this process unreliable. With the advent of interval training, monitoring became more systematic. However, imprecision in the measurement of heart rate (HR) evolved interval training toward index workouts, where the main monitored parameter was average time required to complete index workouts. These measures of training load focused on the external training load, what the athlete could actually do. With the advent of interest from the scientific community, the development of the concept of metabolic thresholds and the possibility of trackside measurement of HR, lactate, VO2, and power output, there was greater interest in the internal training load, allowing better titration of training loads in athletes of differing ability. These methods show much promise but often require laboratory testing for calibration and tend to produce too much information, in too slow a time frame, to be optimally useful to coaches. The advent of the TRIMP concept by Banister suggested a strategy to combine intensity and duration elements of training into a single index concept, training load. Although the original TRIMP concept was mathematically complex, the development of the session RPE and similar low-tech methods has demonstrated a way to evaluate training load, along with derived variables, in a simple, responsive way. Recently, there has been interest in using wearable sensors to provide high-resolution data of the external training load. These methods are promising, but problems relative to information overload and turnaround time to coaches remain to be solved.

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Corrado Lupo, Laura Capranica and Antonio Tessitore

Context:

The assessment of internal training load (ITL) using the session rating of perceived exertion (session RPE) has been demonstrated to provide valuable information, also in team sports. Nevertheless, no studies have investigated the use of this method during youth water polo training.

Purpose:

To evaluate youth water polo training, showing the corresponding level of reliability of the session-RPE method.

Methods:

Thirteen male youth water polo players (age 15.6 ± 0.5 y, height 1.80 ± 0.06 m, body mass 72.7 ± 7.8 kg) were monitored during 8 training sessions (80 individual training sessions) over 10 d. The Edwards summated heart-rate-zone method was used as a reference measure of ITL; the session-RPE rating was obtained using CR-10 scale modified by Foster. The Pearson product–moment was applied to regress the Edwards heart-rate-zone method against CR-10 session RPE for each training session and individual data.

Results:

Analyses reported overall high (r = .88, R 2 = .78) and significant (P < .001) correlations between the Edwards heart-rate and session-RPE methods. Significant correlations were also shown for each training session (r range .69–.92, R 2 range .48–.85, P < .05) and individual data (r range .76–.98, R 2 range .58–.97, P < .05).

Discussion:

The results confirmed that the session-RPE method as an easy and reliable tool to evaluate ITL in youth water polo, allowing coaches to efficiently monitor their training plans.

Open access

Twan ten Haaf, Selma van Staveren, Erik Oudenhoven, Maria F. Piacentini, Romain Meeusen, Bart Roelands, Leo Koenderman, Hein A.M. Daanen, Carl Foster and Jos J. de Koning

Purpose:

To investigate whether monitoring of easily measurable stressors and symptoms can be used to distinguish early between acute fatigue (AF) and functional overreaching (FOR).

Methods:

The study included 30 subjects (11 female, 19 male; age 40.8 ± 10.8 y, VO2max 51.8 ± 6.3 mL · kg–1 · min–1) who participated in an 8-d cycling event over 1300 km with 18,500 climbing meters. Performance was measured before and after the event using a maximal incremental test. Subjects with decreased performance after the event were classified as FOR, others as AF. Mental and physical well-being, internal training load, resting heart rate, temperature, and mood were measured daily during the event. Differences between AF and FOR were analyzed using mixed-model ANOVAs. Logistic regression was used to determine the best predictors of FOR after 3 and 6 d of cycling.

Results:

Fifteen subjects were classified as FOR and 14 as AF (1 excluded). Although total group changes were observed during the event, no differences between AF and FOR were found for individual monitoring parameters. The combination of questionnaire-based changes in fatigue and readiness to train after 3 d cycling correctly predicted 78% of the subjects as AF or FOR (sensitivity = 79%, specificity = 77%).

Conclusions:

Monitoring changes in fatigue and readiness to train, using simple visual analog scales, can be used to identify subjects likely to become FOR after only 3 d of cycling. Hence, we encourage athlete support staff to monitor not only fatigue but also the subjective integrated mental and physical readiness to perform.

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Stuart R. Graham, Stuart Cormack, Gaynor Parfitt and Roger Eston

. Although it is unlikely that a single external or internal training-load measure will describe all the variation in MEI/min and PR Score , alternative variables to those investigated in this study may be able to provide enhanced predictive power. Research has extracted PL activity below 2 m/s from total PL

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Thiago S. Duarte, Danilo L. Alves, Danilo R. Coimbra, Bernardo Miloski, João C. Bouzas Marins and Maurício G. Bara Filho

, such as global positioning system, 11 number of jumps per session, 12 strokes per minute, 13 and type of training. 14 On the other hand, how the athlete answers the workload is conventionally called the internal training load (ITL). 2 Despite the different measures developed, there is still no

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Kizzy Antualpa, Marcelo Saldanha Aoki and Alexandre Moreira

’s data in the final analysis, the following requirements were adopted: 1) completion of at least 75% of the training program in each of the periods investigated; 2) completion of the session rating of perceived exertion to determine the internal training load and the daily questionnaire for URTI; 3

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Petros G. Botonis, Ioannis Malliaros, Gavriil G. Arsoniadis, Theodoros I. Platanou and Argyris G. Toubekis

internal training load responses of long-interval front crawl swimming (3 ×4 min; SW) with water polo–specific drills (counterattacks; CA) in a scheme of 3∶2, wherein 3 is the number of attackers and 2 the number of defenders, using the same time duration (ie, 3 bouts of 4-min exercise separated by 3 min

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Youri Geurkink, Gilles Vandewiele, Maarten Lievens, Filip de Turck, Femke Ongenae, Stijn P.J. Matthys, Jan Boone and Jan G. Bourgois

elicits an internal physiological stress, or the internal training load. However, the internal training load is not only dependent on the imposed external training load, but also on the players’ individual characteristics (ICs). 2 It is possible to assess the internal training load through quantification

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Andrea Fusco, Christine Knutson, Charles King, Richard P. Mikat, John P. Porcari, Cristina Cortis and Carl Foster

measures challenging for assessing internal training load (TL). Subjective measures of exercise intensity, such as the rating of perceived exertion (RPE) 4 and session RPE (sRPE), 5 have become widely used to quantify internal TL, as they can be easily administered and interpreted. The TL is calculated

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Miranda J. Menaspà, Paolo Menaspà, Sally A. Clark and Maurizio Fanchini

online AMS application for assessing s-RPE was shown to be a valid indicator of internal training load and can be used in elite sport. Acknowledgments The authors would like to thank the coach and each athlete who participated in this study. References 1. Foster C , Florhaug JA , Franklin J , et